Experiences of Teachers, Students, and Administrators in One Exemplary ‘EcoSchool’: An Exploration of Best Practices and Challenges in Environmental Education
Bibliographic record
Abstract
This presentation features the main findings and recommendations of an in-depth exploratory case study of teachers, students and administrators in one exemplary EcoSchool. This study focused on the implementation strategies, experiences of teacher members, and involvement of students in an environmental education (EE) program called EcoSchools. Data were collected during the in 2015 – 2016 academic year within one Gold certified secondary school in southern Ontario. Data sources include document analysis of seven years of Eco certification portfolios, observations of EcoTeam activities, and semi-structured interviews with 15 teachers, administrators, and students. The school offered insight into the successes and challenges of EcoSchool implementation. Emergent positive outcomes include strong administrative support, staff reducing paper usage, student leadership opportunities, and rewarding stewardship projects. Data revealed major challenges with low student involvement, reducing food waste, and monitoring energy conservation habits in a secondary school setting. This study offers insights into strategies to overcome challenges and successful practices that may engage students in authentic environmental education in secondary school contexts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".